DESCRIPTION: (Applicant's Description) While adenocarcinoma of the prostate is the most commonly diagnosed cancer in American men and the second leading cause of cancer mortality, technologic and engineering advances have not pushed diagnosis or treatment methods forward when compared to, for example, brain cancers. The objective of this research and development project is to create a methodology suitable for spatially accurate image-guided diagnosis and treatment of prostate cancer. Our method is based around the newly emerging techniques in interventional MRI (IMRI) and nuclear imaging, including image registration, image guided biopsy, and direct monitoring of thermal therapy. To test our methodology, we will perform careful validation testing in an experimental animal model to justify future clinical trials and clinical evaluation in patients. Specifically, we will acquire MRI volume scans of the pelvis and register these images with nuclear scans that provide metabolic/monoclonal indicators of disease. This first registration will semi-automatically combine image data sets with markedly different spatial, contrast and SNR characteristics. During guidance to the prostate lesion, we will compare new rapid MRI techniques with improved immunity to motion to existing methods, and we will complete development and validation of two methods for IMRI navigation where the target tissue and the interventional device are ensured to remain in the scan plane. Two methods shown to be feasible for IMRl guided procedures will be integrated with registered data sets to provide both scan planes which always include the interventional tool and the target tissue and a best estimate of the registered data at the same orientation to improve accuracy of placement of the tools into the most appropriate tissue location. Guidance accuracy will be validated. Image registration methods during guidance will provide accurate automated multi-modality resolution between the new rapidly acquired data and previously registered nuclear and MRI data as a method to improve targeted biopsy and treatment. We will develop new methods to visualize information, like the interventional tool trajectory and tissue temperature and validate their accuracy. We will use phantoms when possible, but more importantly, we will create a canine model to provide comparable tissue deformation, perfusion, morphology and organ and physiologic motion expected in human trials. Finally, we will validate accuracy of both our image guided biopsy and image guided minimally invasive treatment under realistic conditions.